code: def mult_dense_train_data():
      mult_dense, mult_target = make_classification(
          n_samples=300,
          n_features=100,
          n_informative=5,
          n_classes=3,
          random_state=0,
      )
      return mult_dense, mult_target
  
file_path: lightning/lightning/impl/tests/conftest.py
imports: import pytest
  import scipy.sparse
  from sklearn.datasets import load_iris
  from lightning.impl.datasets.samples_generator import make_classification
label_desc: Use image node_id 5 for calling a global function with example usage: mult_dense_train_data() and returns: mult_dense,  mult_target